SUO: Laws, Facts, and Contexts
John,
Your paper at http://www.jfsowa.com/pubs/laws.htm
"Laws, Facts, and Contexts: Foundations for
Multimodal Reasoning" is a first rate accomplishment.
Thank you for taking the time to get so much
information into one article. Its a wonderfully
integrative piece of writing.
But I have two questions: First, how can a BDI
model be translated into an NGM?
You gave some algorithms for translating
other systems into NGMs, but not one for
the BDI system you mentioned:
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To formalize Bratman's theory in Kripke-style
model structures, Cohen and Levesque (1990)
extended Kripke's triples to BDI octuples of
the form (<theta>,P,E,Agnt,T,B,G,<Phi>) where:
<Theta> is a set of entities called things;
P is a set of entities called people;
E is a set of event types;
Agnt is a function defined over events, which
specifies some entity in P as the agent of the
event;
T is a set of possible worlds or courses of
events, each of which is a function from a
sequence Z of time points to event types in E;
B(w1,p,t,w2) is a belief accessibility relation,
which relates a course of events w1, a person p,
and a time point t to some course of events w2
that is accessible from w1 according to p's beliefs;
G(w1,p,t,w2) is a goal accessibility relation,
which relates a course of events w1, a person p,
and a time point t to some course of events w2
that is accessible from w1 according to p's goals;
<Phi> is an evaluation function similar to Kripke's <Phi>.
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Second, if an NGM model of a BDI system were
implemented, would it be a good basis architecture
for a question answering system that could capture
WordNet, CoreLex, EVCA and other aspects of a
large ontology for natural language processing
instrumentation?
Third, what else would be needed for such an
architecture to be fully capable of supporting
question answering tasks in natural language?
Thanks,
Rich